Biology subjects

Patil, A.

Publications and source records attributed to Patil, A..

35 records · Page 2Linked to original sources

bioRxiv2023

Organism-Wide Analysis of Sepsis Reveals Mechanisms of Systemic Inflammation

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the impact of sepsis across organs of the body is rudimentary. Here, using mouse models of sepsis, we generate a dynamic, organism-wide map of the pathogenesis of the disease, revealing the spatiotemporal patterns of the effects of sepsis across tissues. These data revealed two interorgan mechanisms key in sepsis. First, we discover a simplifying principle in the systemic behavior of the cytokine network during sepsis, whereby a hierarchical cytokine circuit arising from the pairwise effects of TNF plus IL-18, IFN-{gamma}, or IL-1{beta} explains half of all the cellular effects of sepsis on 195 cell types across 9 organs. Second, we find that the secreted phospholipase PLA2G5 mediates hemolysis in blood, contributing to organ failure during sepsis. These results provide fundamental insights to help build a unifying mechanistic framework for the pathophysiological effects of sepsis on the body.

immunology↗

bioRxiv2023

BRCA1 expression, its correlation with clinicopathological features and response to neoadjuvant chemotherapy in high grade serous ovarian cancer from an Indian centre

In high grade serous ovarian cancers (HG-SOC), BRCA1/2 mutations have been reported as the most predominant mutations by various studies. However, the non-mutational mechanisms of BRCA pathway inactivation in HG-SOC are unclear. We aimed to evaluate BRCA1 inactivation by estimating its expression along with its repressor in primary and neoadjuvant chemotherapy (NACT) treated HG-SOC tumors with known therapeutic response. The expression pattern of BRCA1 protein was evaluated by immunohistochemistry (IHC) in 119 cases of HG-SOC from a hospital cohort consisting of primary (N= 69) and NACT treated (N=50) tumors. Histological patterns (SET), stromal infiltration by lymphocytes (sTILs) and chemotherapy response score (CRS) were estimated by microscopic examination. Gene expression levels of BRCA1, and its repressor ID4 was estimated by qPCR. Association of BRCA1 protein and mRNA with clinicopathological features was studied. Relevance of the BRCA1/ID4 ratio was evaluated in tumors with different CRS. BRCA1 protein expression was observed in 12% of primary and 19% of NACT treated HG-SOC tumors. Moderate concordance was observed between BRCA1 protein and mRNA expression (AUC-0.677). High BRCA1 mRNA expression was significantly associated with more frequent SET pattern (p=0.024), higher sTILs density (p=0.042), increased mitosis (p=0.028). BRCA1 negative tumors showed higher expression of ID4 though not statistically significant. Higher BRCA1/ID4 ratio was associated with high sTILs density in primary (p=0.042) and NACT treated tumors (p=0.040). Our findings show the utility of BRCA1/ID4 ratio to predict neoadjuvant therapy response, which needs further evaluation in larger cohort with long term outcomes.

cancer biology↗

bioRxiv2023

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

genomics↗

bioRxiv2022

How woodcocks produce the most brilliant white plumage patches among the birds

Until recently, and when compared with diurnal birds that use contrasting plumage patches and complex feather structures to convey visual information, communication in nocturnal species was considered to follow acoustic and chemical channels. However, many nocturnal birds have evolved intensely white plumage patches within otherwise inconspicuous plumages. We used spectrophotometry, electron microscopy, and optical modelling to explain the mechanisms producing bright white tail feather tips of the Eurasian woodcock Scolopax rusticola. Their diffuse reflectance was [~]30% higher than any previously measured feather. This intense reflectance is the result of incoherent light scattering from a disordered nanostructure composed of keratin and air within the barb rami. In addition, the flattening, thickening, and arrangement of those barbs creates a Venetian-blind-like macrostructure that enhances the surface area for light reflection. We suggest that the woodcocks have evolved these bright white feather patches for long-range visual communication in dimly lit environments.

ecology↗

bioRxiv2022

Kinase-independent activity of DYRK1A promotes viral entry of highly pathogenic human coronaviruses

Identifying host genes essential for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to reveal novel drug targets and further our understanding of coronavirus disease 2019 (COVID-19). We previously performed a genome-wide CRISPR/Cas9 screen to identify pro-viral host factors for highly pathogenic human coronaviruses. Very few host factors were required by diverse coronaviruses across multiple cell types, but DYRK1A was one such exception. Although its role in coronavirus infection was completely unknown, DYRK1A encodes Dual Specificity Tyrosine Phosphorylation Regulated Kinase 1A and regulates cell proliferation, and neuronal development, among other cellular processes. Interestingly, individuals with Down syndrome overexpress DYRK1A 1.5-fold and exhibit 5-10x higher hospitalization and mortality rates from COVID-19 infection. Here, we demonstrate that DYRK1A regulates ACE2 and DPP4 transcription independent of its catalytic kinase function to support SARS-CoV, SARS-CoV-2, and MERS-CoV entry. We show that DYRK1A promotes DNA accessibility at the ACE2 promoter and a putative distal enhancer, facilitating transcription and gene expression. Finally, we validate that the pro-viral activity of DYRK1A is conserved across species using cells of monkey and human origin and an in vivo mouse model. In summary, we report that DYRK1A is a novel regulator of ACE2 and DPP4 expression that may dictate susceptibility to multiple highly pathogenic human coronaviruses. Whether DYRK1A overexpression contributes to heightened COVID-19 severity in individuals with Down syndrome through ACE2 regulation warrants further future investigation.

microbiology↗

bioRxiv2022

Heterotypic Endosomal Interactions Drive Emergent Early Endosomal Maturations

Endosomal maturation is critical for robust and timely cargo transport to specific cellular compartments. The most prominent model of early endosomal maturation involves phosphoinositide-driven gain or loss of specific proteins on individual endosomes, emphasising an autonomous and stochastic description. However, limitations in fast, volumetric imaging long hindered direct whole-cell measurements of absolute numbers of maturation events. Here, we use lattice light-sheet imaging and bespoke automated analysis to track individual very early (APPL1-positive) and early (EEA1-positive) endosomes over the entire population, demonstrating that direct interendosomal contact drives maturation. Using fluorescence lifetime, we show that this interaction is underpinned by asymmetric EEA1 binding to very early and early endosomes through its N- and C-termini, respectively. In combination with agent-based simulation that confirms a trigger-and-convert model, our findings indicate that APPL1-to EEA1-positive maturation is driven not by autonomous events but by heterotypic EEA1-mediated interactions, providing a mechanism for temporal and population-level control of maturation.

biophysics↗

bioRxiv2022

NETISCE: A Network-Based Tool for Cell Fate Reprogramming

The search for effective therapeutic targets in fields like regenerative medicine and cancer research has generated interest in cell fate reprogramming. This cellular reprogramming paradigm can drive cells to a desired target state from any initial state. However, methods for identifying reprogramming targets remain limited for biological systems that lack large sets of experimental data or a dynamical characterization. We present NETISCE, a novel computational tool for identifying cell fate reprogramming targets in static networks. In combination with machine learning algorithms, NETISCE estimates the attractor landscape and predicts reprogramming targets using Signal Flow Analysis and Feedback Vertex Set Control, respectively. Through validations in studies of cell fate reprogramming from developmental, stem cell, and cancer biology, we show that NETISCE can predict previously identified cell fate reprogramming targets and identify potentially novel combinations of targets. NETISCE extends cell fate reprogramming studies to larger-scale biological networks without the need for full model parameterization and can be implemented by experimental and computational biologists to identify parts of a biological system relevant to the desired reprogramming task.

systems biology↗

bioRxiv2021

Systematic dissection of a complex gut bacterial community

Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

microbiology↗

bioRxiv2021

In vivo augmentation of a complex gut bacterial community

Efforts to model the human gut microbiome in mice have led to important insights into the mechanisms of host-microbe interactions. However, the model communities studied to date have been defined or complex but not both, limiting their utility. In accompanying work, we constructed a complex synthetic community (104 strains, hCom1) containing the most common taxa in the human gut microbiome. Here, we used an iterative experimental process to improve hCom1 by filling open metabolic and/or anatomical niches. When we colonized germ-free mice with hCom1 and then challenged it with a human fecal sample, the consortium exhibited surprising stability; 89% of the cells and 58% of the taxa derive from the original community, and the pre- and post-challenge communities share a similar overall structure. We used these data to construct a second version of the community, adding 22 strains that engrafted following fecal challenge and omitting 7 that dropped out (119 strains, hCom2). In gnotobiotic mice, hCom2 exhibited increased stability to fecal challenge and robust colonization resistance against pathogenic Escherichia coli. Mice colonized by hCom2 versus human feces are similar in terms of microbiota-derived metabolites, immune cell profile, and bacterial density in the gut, suggesting that this consortium is a prototype of a model system for the human gut microbiome.

microbiology↗

bioRxiv2020

CellKb Immune: a manually curated database of mammalian immune marker gene sets optimized for rapid cell type identification

Using single-cell RNA sequencing, it is now possible to get the detailed gene expression pattern in each cell for millions of cells in a single experiment under varying conditions. Annotating cells by assigning a type or state to them is important for correct interpretation of results. In spite of current advances in technology, assigning cell types in single-cell datasets remains a bottleneck due to the lack of a comprehensive reference database and an accurate search method in a single tool. CellKb Immune is a knowledgebase of manually collected, curated and annotated marker gene sets representing cell types in the immune response in mouse. It allows users to find matching cell types in literature given a list of genes. We evaluated the contents and search methodology of CellKb Immune using a leave-one-out approach. We further used CellKb Immune to annotate previously defined marker gene sets from a bulk RNA-seq dataset to confirm its accuracy and coverage. CellKb Immune provides an easy-to-use online tool with a reliable method to find matching cell types and annotate cells in single-cell experiments. It is available at https://www.cellkb.com/immune.

bioinformatics↗

bioRxiv2020

Combination of photoactivation with lattice light-sheet imaging allows visualizing complex dorsal ruffling dynamics

Membrane protrusions that occur on the dorsal surface of a cell are an excellent experimental system to study actin machinery at work in a living cell. Small GTPase Rac1 controls the membrane protrusions that form and encapsulate extracellular volumes to perform pinocytic or phagocytic functions. Here, capitalizing on rapid volumetric imaging capabilities of lattice light-sheet microscopy (LLSM), we describe optogenetic approaches using photoactivable Rac1 (PA-Rac1) for controlled ruffle generation. We demonstrate that PA-Rac1 activation needs to be continuous, suggesting a threshold local concentration for sustained actin polymerization leading to ruffling. We show that Rac1 activation leads to actin assembly at the dorsal surface of the cell membrane that result in sheet-like protrusion formation without any requirement of a template. Further, this approach can be used to study the complex morpho-dynamics of the protrusions or to investigate specific proteins that may be enriched in the ruffles. Deactivating PA-Rac1 leads to complex contractile processes resulting in formation of macropinosomes. Using multicolour imaging in combination with these approaches, we find that Myo1e specifically is enriched in the ruffles.

biophysics↗

bioRxiv2020

FEATS: Feature selection based clustering of single-cell RNA-seq data

Advances in next-generation sequencing (NGS) have made it possible to carry out transcriptomic studies at single-cell resolution and generate vast amounts of single-cell RNA-seq data rapidly. Thus, tools to analyze this data need to evolve as well to improve accuracy and efficiency. We present FEATS, a python software package that performs clustering on single-cell RNA-seq data. FEATS is capable of performing multiple tasks such as estimating the number of clusters, conducting outlier detection, and integrating data from various experiments. We develop a univariate feature selection based approach for clustering, which involves the selection of top informative features to improve clustering performance. This is motivated by the fact that cell types are often manually determined using the expression of only a few known marker genes. On a variety of single-cell RNA-seq datasets, FEATS gives superior performance compared to the current tools, in terms of adjusted rand index (ARI) and estimating the number of clusters. In addition to cluster estimation, FEATS also performs outlier detection and data integration while giving an excellent computational performance. Thus, FEATS is a comprehensive clustering tool capable of addressing the challenges during the clustering of single-cell RNA-seq data. The installation instructions and documentation of FEATS is available at https://edwinv87.github.io/feats/.

bioinformatics↗

bioRxiv2020

Renal carcinoma is associated with increased risk of coronavirus infections

The current pandemic COVID-19 has affected most severely to the people with old age, or with comorbidities such as hypertension, diabetes mellitus, chronic kidney disease, COPD, and cancers. Cancer patients are twice more likely to contract the disease because of the malignancy or treatment-related immunosuppression; hence identification of the vulnerable population among these patients is essential. It is speculated that along with ACE2, other auxiliary proteins (DPP4, ANPEP, ENPEP, TMPRSS2) might facilitate the entry of coronaviruses in the host cells. We took a bioinformatics approach to analyze the gene and protein expression data of these coronavirus receptors in human normal and cancer tissues of multiple organs. Here, we demonstrated an extensive RNA and protein expression profiling analysis of these receptors across solid tumors and normal tissues. We found that among all, renal tumor and normal tissues exhibited increased levels of ACE2, DPP4, ANPEP, and ENPEP. Our results revealed that TMPRSS2 may not be the co-receptor for coronavirus in renal carcinoma patients. The receptors’ expression levels were variable in different tumor stage, molecular and immune subtypes of renal carcinoma. In clear cell renal cell carcinomas, coronavirus receptors were associated with high immune infiltration, markers of immunosuppression, and T cell exhaustion. Our study indicates that CoV receptors may play an important role in modulating the immune infiltrate and hence cellular immunity in renal carcinoma. As our current knowledge of pathogenic mechanisms will improve, it may help us in designing focused therapeutic approaches.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2020

Role of Prefrontal Cortex during Sudoku task: fNIRS study

Sudoku is a popular leisure time activity that involves no math, but is based on logic based combinatorial number placement in a matrix. Many studies have been dedicated towards finding an algorithm to solve Sudoku but investigation of the neural substrates involved in Sudoku has been challenging. It is difficult to measure the brain activity during 9x9 Sudoku using traditional fMRI technique due to the procedural constraints. 16 optodes fNIRS (functional near infrared spectroscopy) forms an excellent alternative to study the activity of prefrontal cortex (PFC) during Sudoku task. Sudoku task was divided into two steps to understand the differential function of the PFC while applying heuristic rules. Classical two-way ANOVA as well as General Linear Model based approach was used to analyze the data. 28-noise free recording from right-handed participants revealed increased activity in all 16 optode locations during step 1 (3 x 3 subgrids) and step 2 (easy level 9x9 Sudoku) as compared to rest. Contrasting the step2-step1 revealed that medial regions of PFC were preferentially activated. These findings suggest the role of these regions, while applying multiple heuristic rules to solve 9x9 Sudoku puzzle. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/115121v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@88c44eorg.highwire.dtl.DTLVardef@1100737org.highwire.dtl.DTLVardef@149b4a1org.highwire.dtl.DTLVardef@1f1d055_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThis is first fNIRS study that tried to unravel the role of PFC during Sudoku task. C_LIO_LIUniquely divided the Sudoku task into two steps to understand the differential role of PFC while applying multiple heuristic rules. C_LIO_LIBoth the medial and lateral regions of PFC are activated during Sudoku task. C_LIO_LIHowever, the medial regions of PFC play a differential role, especially when we consider the row and the column rule of Sudoku. C_LI

neuroscience↗

bioRxiv2019

Genome-wide CRISPR Screens Reveal Genetic Mediators of Cereblon Modulator Toxicity in Primary Effusion Lymphoma

Genome-wide CRISPR/Cas9 screens represent a powerful approach to study mechanisms of drug action and resistance. Cereblon modulating agents (CMs) have recently emerged as candidates for therapeutic intervention in primary effusion lymphoma (PEL), a highly aggressive cancer caused by Kaposis sarcoma-associated herpesvirus. CMs bind to cereblon (CRBN), the substrate receptor of the cullin-RING type E3 ubiquitin ligase CRL4CRBN, and thereby trigger the acquisition and proteasomal degradation of neosubstrates. Downstream mechanisms of CM toxicity are incompletely understood, however. To identify novel CM effectors and mechanisms of CM resistance, we performed positive selection CRISPR screens using three CMs with increasing toxicity in PEL: lenalidomide (LEN), pomalidomide (POM), and CC-122. Results identified several novel modulators of the activity of CRL4CRBN. The number of genes whose inactivation confers resistance decreases with increasing CM efficacy. Only inactivation of CRBN conferred complete resistance to CC-122. Inactivation of the E2 ubiquitin conjugating enzyme UBE2G1 also conferred robust resistance against LEN and POM. Inactivation of additional genes, including the Nedd8-specific protease SENP8, conferred resistance to only LEN. SENP8 inactivation indirectly increased levels of unneddylated CUL4A/B, which limits CRL4CRBN activity in a dominant negative manner. Accordingly, sensitivity of SENP8-inactivated cells to LEN is restored by overexpression of CRBN. In sum, our screens identify several novel players in CRL4CRBN function and define pathways to CM resistance in PEL. These results provide rationale for increasing CM efficacy upon patient relapse from a less efficient CM. Identified genes could finally be developed as biomarkers to predict CM efficacy in PEL and other cancers.\n\nKey PointsO_LIGenome-wide CRISPR/Cas9 screens identify novel mediators of resistance to lenalidomide, pomalidomide and CC-122 in PEL cells.\nC_LIO_LIUBE2G1 and SENP8 are modulators of CRL4CRBN and their inactivation drives resistance to CMs in PEL-derived cell lines.\nC_LI

cancer biology↗

bioRxiv2018

E74 like ETS transcription factor 3 (ELF3) is a negative regulator of epithelial-mesenchymal transition in bladder carcinoma

Transcription factors are known to be commonly deregulated in various cancers. The E74 like ETS transcription factor 3 (ELF3) expression is restricted to epithelial tissue. In the present study, we evaluated the role of ELF3 in the pathogenesis of bladder carcinoma (BCa) using cell line model. The cell lines with low expression of ELF3 showed increased expression of mesenchymal markers and decreased expression of epithelial markers. Immunofluorescence and immunohistochemical analysis of ELF3 showed selective expression in low-grade BCa cell lines and tumor tissues, respectively. We demonstrated that overexpression of ELF3 in UMUC3, a mesenchymal BCa cell line resulted in reduced invasion and decreased expression of mesenchymal markers. Furthermore, using publicly available data, we found that low expression of ELF3 was associated with increased risk and poor overall survival rate in BCa. In conclusion, ELF3-modulated reversal of EMT might be a useful strategy in the treatment of bladder cancer.

cancer biology↗

bioRxiv2018

Rapid Whole Cell Imaging Reveals An APPL1-Dynein Nexus That Regulates Stimulated EGFR Trafficking

Multicellular life processes such as proliferation and differentiation depend on cell surface signaling receptors that bind ligands generally referred to as growth factors. Recently, it has emerged that the endosomal system provides rich signal processing capabilities for responses elicited by these factors [1-3]. At the single cell level, endosomal trafficking becomes a critical component of signal processing, as exemplified by the epidermal growth factor (EGF) receptors of the receptor tyrosine kinase family. EGFRs, once activated by EGF, are robustly trafficked to the phosphatase-enriched peri-nuclear region (PNR), where they are dephosphorylated [4-8]. However, the details of the mechanisms regulating the movements of stimulated EGFR in time and space, i.e., towards the PNR, are not known. What endosomal regulators provide specificity to EGFR? Do modifications to the receptor upon stimulation regulate its trafficking? To understand the events leading to EGFR translocation, and especially the early endosomal dynamics that immediately follow EGFR internalization, requires the real-time, long-term, whole-cell imaging of multiple elements. Here, exploiting the advantages of lattice light-sheet microscopy [9], we show that the binding of EGF by its receptor, EGFR, triggers a transient calcium increase that peaks by 30 s, causing the desorption of APPL1 from pre-existing endosomes within one minute, the rebinding of liberated APPL1 to EGFR within three minutes, and the dynein-dependent translocation of APPL1-EGF-bearing endosomes to the PNR within five minutes. The novel, cell spanning, fast acting network that we reveal integrates a cascade of events dedicated to the cohort movement of activated EGFR receptors. Our findings support the intriguing proposal that certain endosomal pathways have shed some of the stochastic strategies of traditional trafficking, and have evolved behaviors whose predictability is better suited to signaling [10, 11]. Work presented here demonstrates that our whole cell imaging approach can be a powerful tool in revealing critical transient interactions in key cellular processes such as receptor trafficking.

cell biology↗